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On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor.author Lopez-de-Ipiña, Karmele
dc.contributor.author Alonso, Jesús B.
dc.contributor.author Travieso, Carlos M.
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Egiraun, Harkaitz
dc.contributor.author Faundez-Zanuy, Marcos
dc.contributor.author Ezeiza, Aitzol
dc.contributor.author Barroso, Nora
dc.contributor.author Ecay-Torres, Miriam
dc.contributor.author Martinez-Lage, Pablo
dc.contributor.author Martinez de Lizardui, Unai
dc.date.accessioned 2013-06-27T15:12:56Z
dc.date.available 2013-06-27T15:12:56Z
dc.date.created 2013
dc.date.issued 2013
dc.identifier.citation LÓPEZ-DE-IPIÑA, K., ALONSO, J.-., TRAVIESO, C.M., SOLÉ CASALS, J., EGIRAUN, H., FAUNDEZ-ZANUY, M., EZEIZA, A., BARROSO, N., ECAY-TORRES, M., MARTINEZ-LAGE, P. and DE LIZARDUI, U.M., 2013. On the selection of non-invasive methods based on speech analysis oriented to automatic Alzheimer disease diagnosis. Sensors (Switzerland), 13(5), pp. 6730-6745. ca_ES
dc.identifier.issn 1424-8220
dc.identifier.uri http://hdl.handle.net/10854/2286
dc.description.abstract The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients. ca_ES
dc.format application/pdf
dc.format.extent 16 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher MDPI ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/ ca_ES
dc.subject.other Alzheimer, Malaltia d' ca_ES
dc.subject.other Processament de la parla ca_ES
dc.title On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis ca_ES
dc.type info:eu-repo/semantics/article ca_ES
dc.identifier.doi https://doi.org/doi:10.3390/s130506730
dc.relation.publisherversion http://www.mdpi.com/1424-8220/13/5
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES
dc.type.version info:eu-repo/publishedVersion ca_ES
dc.indexacio Indexat a SCOPUS
dc.indexacio Indexat a WOS/JCR ca_ES

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